library(tidyverse)
library(purrrlyr)
library(plotly)
library(themebg)
# x <- dirr::get_rds("../data/tidy")
x <- dirr::get_rds_s3("warfarin-annual-report", "data/tidy/")
p <- data_daily %>%
filter(warfarin_day <= 10) %>%
dmap_at("warfarin_day", as.integer) %>%
left_join(data_warfarin[c("millennium.id", "group", "initiation", "indication_group")], by = "millennium.id") %>%
ggplot(aes(x = factor(warfarin_day), y = med.dose, color = group)) +
geom_boxplot() +
xlab("Day of therapy") +
ylab("Warfarin dose (mg)") +
scale_color_brewer("Group", palette = "Set1") +
theme_bg()
ggplotly(p, dynamicTicks = TRUE)
Distribution of warfarin dose by day of therapy
p <- data_daily %>%
filter(warfarin_day <= 10,
med.dose > 0,
!is.na(inr)) %>%
# dmap_at("warfarin_day", as.integer) %>%
left_join(data_warfarin[c("millennium.id", "group", "initiation", "indication_group")], by = "millennium.id") %>%
ggplot(aes(x = med.dose, y = inr)) +
geom_point(aes(color = group), shape = 1) +
xlab("Warfarin dose (mg)") +
ylab("INR") +
scale_color_brewer("Group", palette = "Set1") +
theme_bg()
ggplotly(p, dynamicTicks = TRUE)
Relationship between warfarin dose and INR